Mining Frequent Trajectory Patterns and Regions-of-Interest from Flickr Photos

Flickr represents a massive opportunity to mine valuable human movement data from geo-tagged photos. However, existing Flickr trajectory data mining research has not considered mining frequent trajectory patterns whilst also considering the temporal domain. Therefore, a significant opportunity exists to demonstrate the application of a pattern mining algorithm to a large geo-tagged photo dataset. Thus, we present a novel application of the trajectory pattern mining algorithm to a 2012 Flickr dataset of Australia and encompassing state, Queens land. In our experiments we show that many interesting, previously unknown patterns discovered through our framework. Our framework is able to discover expected major landmarks such as cities and tourist attractions. In addition, we make the notable discover of what is theorized to be valuable tourist travel information about sequential movements between hot-spot attractions.